Cutting the tree

Cluster Analysis in R

Dmitriy Gorenshteyn

Lead Data Scientist, Memorial Sloan Kettering Cancer Center

Coloring the dendrogram - height

library(dendextend)

dend_players <- as.dendrogram(hc_players)

dend_colored <- color_branches(dend_players, h = 15)

plot(dend_colored)

Coloring the dendrogram - height

library(dendextend)

dend_players <- as.dendrogram(hc_players)

dend_colored <- color_branches(dend_players, h = 15)

plot(dend_colored)

Coloring the dendrogram - height

library(dendextend)

dend_players <- as.dendrogram(hc_players)

dend_colored <- color_branches(dend_players, h = 10)

plot(dend_colored)

Coloring the dendrogram - K

library(dendextend)

dend_players <- as.dendrogram(hc_players)

dend_colored <- color_branches(dend_players, k = 2)

plot(dend_colored)

cutree() using height

cluster_assignments <- cutree(hc_players, h = 15)

print(cluster_assignments)
[1] 1 1 1 1 2 2

library(dplyr)
players_clustered <- mutate(players, cluster = cluster_assignments)

print(players_clustered)
      x     y cluster
  <dbl> <dbl>   <int>
1    -1     1       1
2    -2    -3       1
3     8     6       1
4     7    -8       1
5   -12     8       2
6   -15     0       2

Let's practice!

Cluster Analysis in R